spark api cisco

value of each element is mapped to a series of values by the input function, and the values then form a series of new kv pairs with the key in the original RDD.Examplescala> val A = Sc.parallelize (List ((), (3,4), (3,6))) Scala> Val b = a.flatmapvalues (x=>x.to (5)) Scala>= Array ((1,3), (1,4), (1,5), (3,4), (3,5))In the above example, the value of each element in the RDD is converted to a sequence (from its current value to 5), such as the first KV pair (for example), and its value of 2 is co

1. RDDThe RDD (Resilient distributed dataset Elastic distributed data Set) is the abstract data structure type in spark, which is represented as an rdd in spark. From a programmatic point of view, an RDD can be viewed simply as an array. The difference between an ordinary array is that the data in the RDD is partitioned, so that data from different partitions can be distributed across different machines and

updated. The active node continues to send its own property value to the neighboring node.Superstep 2: Node 3 accepts the information and calculates that the other node does not receive the message or receives it but does not compute it, so only node 3 is active and sends the message next.Superstep 3: Nodes 2 and 4 receive messages but do not calculate so inactive, all nodes are inactive, so the calculation ends.There are two core functions in the Pregel Computing framework: The SendMessage fun

sequence (from its current value to 5), such as the first KV pair (for example), and its value of 2 is converted to 2,3,4,5. Then it is formed a series of new KV pairs (1,3), (1,4), (1,5) with the original KV key.ReduceReduce passes the element 22 in the RDD to the input function, generating a new value, the newly generated value and the next element of the RDD being passed to the input function until there is only one value at the end.Examplescala> val c = sc.parallelize(1 to 10)scala> c.reduc

This document is edited by Cmd Markdown, the original link: https://www.zybuluo.com/jewes/note/35032What is an RDD?The RDD is an abstract data structure type in spark, and any data is represented as an rdd in spark. From a programmatic point of view, an RDD can be viewed simply as an array. Unlike normal arrays, the data in the RDD is partitioned, so that data from different partitions can be distributed ac

1 PrefaceCombinebykey is a method that cannot be avoided using spark, and is always invoked, either intentionally or unintentionally, directly or indirectly to it. It can be literally known that it has the function of aggregation, and for this reason do not want to do too much explanation, because it is very simple, because Reducebykey, Aggregatebykey, Foldbykey and other functions are to use it to achieve.Combinebykey is a highly abstract aggregation

1. Create a new MAVEN projectAfter the initial MAVEN project is complete, the initial configuration (Pom.xml) is as follows:2. Configure MavenCreate a new Spark core library in the project3. Create a new Java classCreate a new Java class and write to the Spark (Java API) code:import org.apache.spark.api.java.*;import org.apache.spark.SparkConf;import org.apache.s

")). Show ())println("---------------------------DSL---------------------------------")println(Parquet.where (' Age > '). Select ('Name). Show ())println("-----------------------------SQL-------------------------------") Parquet.registertemptable ("Parquet") Sql.sql ("SELECT name from Parquet where age >").Map(P ="Name:"+ P(0). Collect (). foreach (println)JSON format test:Val sc =NewSparkcontext () Val sql =NewSqlContext (SC)ImportSql.implicits._ val json = sql.jsonfile (args(0))println("------

execute SH:ImportJava.io.File;ImportJava.text.SimpleDateFormat;Importjava.util.Date; Public classJavashellinvoker {Private Static FinalString executeshelllogfile = "./executeshell_%s_%s.log"; Public intExecuteshell (String Shellcommandtype, String Shellcommand, String args)throwsException {intSuccess = 0; Args= (Args = =NULL) ? "": args; String Now=NewSimpleDateFormat ("Yyyy-mm-dd"). Format (NewDate ()); File LogFile=NewFile (String.Format (Executeshelllogfile, Shellcommandtype, now)); Process

This article goes on to explain the Rdd API, explaining the APIs that are not very easy to understand, and this article will show you how to introduce external functions into the RDD API, and finally learn about the Rdd API, and we'll talk about some of the Scala syntax associated with RDD development.1) Aggregate (Zerovalue) (Seqop,combop)This function, like the

)).Map(_.split ("::") match { case Array (user, item, rate) = Rating (User.toint, Item.toint, rate.todouble)})Set number of stealth factors, number of iterationsVal Rank= 10Val numiterations= 5//CallALSClass ofTrainMethods, passing in the data to be trained and so on model trainingVal Model=ALS.Train(ratings, rank, numiterations, 0.01)Convert the training data into(User,item)Format to be used as a test model for predicting data (collaborative filtering of model predictions when the incoming(Use

Spark Machine Learning Mllib Series 1 (for Python)--data type, vector, distributed matrix, API Key words: Local vector,labeled point,local matrix,distributed Matrix,rowmatrix,indexedrowmatrix,coordinatematrix, Blockmatrix.Mllib supports local vectors and matrices stored on single computers, and of course supports distributed matrices stored as RDD. An example of a supervised machine learning is called a la